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arXiv · 1711.06636

Segmenting Brain Tumors with Symmetry

Hejia Zhang·Xia Zhu·Theodore L. Willke
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Abstract

We explore encoding brain symmetry into a neural network for a brain tumor segmentation task. A healthy human brain is symmetric at a high level of abstraction, and the high-level asymmetric parts are more likely to be tumor regions. Paying more attention to asymmetries has the potential to boost the performance in brain tumor segmentation. We propose a method to encode brain symmetry into existing neural networks and apply the method to a state-of-the-art neural network for medical imaging segmentation. We evaluate our symmetry-encoded network on the dataset from a brain tumor segmentation challenge and verify that the new model extracts information in the training images more efficiently than the original model.

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Hejia Zhang, Xia Zhu, Theodore L. Willke. 2017-11-17. Segmenting Brain Tumors with Symmetry. https://arxiv.org/abs/1711.06636

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